American Institute of Mathematical Sciences

Advanced
June  2009, 4(2): i-v. doi: 10.3934/nhm.2009.4.2i

Preface

Georges Bastin 1, , Alexandre M. Bayen 2, , Ciro D'Apice 3, , Xavier Litrico 4, and  Benedetto Piccoli 5,

1. 

Center for Systems Engineering and Applied Mechanics (CESAME), Department of Mathematical Engineering, Université catholique de Louvain, 4, Avenue G. Lemaître, 1348 Louvain-la-Neuve
2. 

Department of Civil and Environmental Engineering, 711 Davis Hall, University of California, Berkeley, CA 94720-1710, United States
3. 

Dipartimento di Ingegneria dell'Informazione e Matematica Applicata, via Ponte Don Melillo, 84084 Fisciano (SA)
4. 

Cemagref, UMR G-EAU, 361 rue JF Breton, F-34196 Montpellier Cedex 5
5. 

Istituto per le Applicazioni del Calcolo, Viale del Policlinico 137, 00161 Rome

Published  June 2009

1. Introduction: Management of canal networks at the age of information technology. With the miniaturization of sensors and their decreasing costs, the paradigm of instrumentation of the built infrastructure and the environment has now been underway for several years, leading to numerous successful and sometimes spectacular realizations such as the instrumentation of the Golden Gate with wire- less sensors a few years ago. The convergence of communication, control and sensing on numerous platforms including multi-media platforms has enabled engineers to augment physical infrastructure systems with an information layer, capable of real- time monitoring, with particular success in the health monitoring community. This paradigm has reached a level of maturity, revealed by the emergence of numerous technologies usable to monitor the built infrastructure. Supervisory Control And Data Acquisition (SCADA) systems are a perfect example of such infrastructure, which integrate sensing, communication and control. In the context of management of irrigation networks, the impact of this technology on the control of such systems has the potential of significantly improving efficiency of operations.

For more information please click the “Full Text” above
Keywords: Irrigation channels..
Mathematics Subject Classification: Primary: 35L65, 35L50; Secondary: 76B7.
Citation: Georges Bastin, Alexandre M. Bayen, Ciro D'Apice, Xavier Litrico, Benedetto Piccoli. Preface. Networks and Heterogeneous Media, 2009, 4 (2) : i-v. doi: 10.3934/nhm.2009.4.2i
[1]

Qing Sun. Irrigable measures for weighted irrigation plans. Networks and Heterogeneous Media, 2021, 16 (3) : 493-511. doi: 10.3934/nhm.2021014
[2]

Rudy R. Negenborn, Peter-Jules van Overloop, Tamás Keviczky, Bart De Schutter. Distributed model predictive control of irrigation canals. Networks and Heterogeneous Media, 2009, 4 (2) : 359-380. doi: 10.3934/nhm.2009.4.359
[3]

Maria Colombo, Antonio De Rosa, Andrea Marchese, Paul Pegon, Antoine Prouff. Stability of optimal traffic plans in the irrigation problem. Discrete and Continuous Dynamical Systems, 2022, 42 (4) : 1647-1667. doi: 10.3934/dcds.2021167
[4]

Tobias Sutter, David Sutter, John Lygeros. Capacity of random channels with large alphabets. Advances in Mathematics of Communications, 2017, 11 (4) : 813-835. doi: 10.3934/amc.2017060
[5]

João M. Lemos, Fernando Machado, Nuno Nogueira, Luís Rato, Manuel Rijo. Adaptive and non-adaptive model predictive control of an irrigation channel. Networks and Heterogeneous Media, 2009, 4 (2) : 303-324. doi: 10.3934/nhm.2009.4.303
[6]

Nadia Bedjaoui, Erik Weyer, Georges Bastin. Methods for the localization of a leak in open water channels. Networks and Heterogeneous Media, 2009, 4 (2) : 189-210. doi: 10.3934/nhm.2009.4.189
[7]

Carlos E. Kenig. The method of energy channels for nonlinear wave equations. Discrete and Continuous Dynamical Systems, 2019, 39 (12) : 6979-6993. doi: 10.3934/dcds.2019240
[8]

Carolyn Mayer, Kathryn Haymaker, Christine A. Kelley. Channel decomposition for multilevel codes over multilevel and partial erasure channels. Advances in Mathematics of Communications, 2018, 12 (1) : 151-168. doi: 10.3934/amc.2018010
[9]

Daniele Andreucci, Dario Bellaveglia, Emilio N.M. Cirillo, Silvia Marconi. Effect of intracellular diffusion on current--voltage curves in potassium channels. Discrete and Continuous Dynamical Systems - B, 2014, 19 (7) : 1837-1853. doi: 10.3934/dcdsb.2014.19.1837
[10]

Jorge P. Arpasi. On the non-Abelian group code capacity of memoryless channels. Advances in Mathematics of Communications, 2020, 14 (3) : 423-436. doi: 10.3934/amc.2020058
[11]

Juan C. Moreno, V. B. Surya Prasath, João C. Neves. Color image processing by vectorial total variation with gradient channels coupling. Inverse Problems and Imaging, 2016, 10 (2) : 461-497. doi: 10.3934/ipi.2016008
[12]

David Karpuk, Anne-Maria Ernvall-Hytönen, Camilla Hollanti, Emanuele Viterbo. Probability estimates for fading and wiretap channels from ideal class zeta functions. Advances in Mathematics of Communications, 2015, 9 (4) : 391-413. doi: 10.3934/amc.2015.9.391
[13]

Virginia González-Vélez, Amparo Gil, Iván Quesada. Minimal state models for ionic channels involved in glucagon secretion. Mathematical Biosciences & Engineering, 2010, 7 (4) : 793-807. doi: 10.3934/mbe.2010.7.793
[14]

Filippo Giuliani. Transfers of energy through fast diffusion channels in some resonant PDEs on the circle. Discrete and Continuous Dynamical Systems, 2021, 41 (11) : 5057-5085. doi: 10.3934/dcds.2021068
[15]

Qiangheng Zhang. Dynamics of stochastic retarded Benjamin-Bona-Mahony equations on unbounded channels. Discrete and Continuous Dynamical Systems - B, 2021  doi: 10.3934/dcdsb.2021293
[16]

Guofen Zhang, Ping Li, Jianfeng Hou, Bo Bai. The zero-error capacity of binary channels with 2-memories. Advances in Mathematics of Communications, 2022  doi: 10.3934/amc.2022009
[17]

Holger Boche, Rafael F. Schaefer. Arbitrarily varying multiple access channels with conferencing encoders: List decoding and finite coordination resources. Advances in Mathematics of Communications, 2016, 10 (2) : 333-354. doi: 10.3934/amc.2016009
[18]

Tehuan Chen, Chao Xu, Zhigang Ren. Computational optimal control of 1D colloid transport by solute gradients in dead-end micro-channels. Journal of Industrial and Management Optimization, 2018, 14 (3) : 1251-1269. doi: 10.3934/jimo.2018052
[19]

Marta Lewicka, Mohammadreza Raoofi. A stability result for the Stokes-Boussinesq equations in infinite 3d channels. Communications on Pure and Applied Analysis, 2013, 12 (6) : 2615-2625. doi: 10.3934/cpaa.2013.12.2615
[20]

Yoora Kim, Gang Uk Hwang, Hea Sook Park. Feedback limited opportunistic scheduling and admission control for ergodic rate guarantees over Nakagami-$m$ fading channels. Journal of Industrial and Management Optimization, 2009, 5 (3) : 553-567. doi: 10.3934/jimo.2009.5.553

2020 Impact Factor: 1.213

Tools

Metrics

  • PDF downloads (73)
  • HTML views (0)
  • Cited by (1)

Other articles
by authors

[Back to Top]

Copyright © 2022 American Institute of Mathematical Sciences | Privacy Policy